Manhattan Plot

les territoires étudiés

Les EPCI

	N	Mean
Population	1249	53424

Les communes des métropoles de Paris, Lyon, Marseille

	N	Mean
Population	324	31986

Les variables utilisées pour l’étude

Thématique Logement

	N	Med	IQR
X1ry_res	1573	85	15
X2ry_res	1573	5.6	11
Vacant_Home	1573	8.4	4.2
Houses	1573	78	32
Flats	1573	21	32
Nb_Rooms_1ry_res	1573	4.4	0.57
House_1ry_res	1573	79	29
Flat_1ry_res	1573	20	28
X1ry_res_bf_1919	1573	16	15
X1ry_res_19.45	1573	7.9	4.7
X1ry_res_46.70	1573	16	9.6
X1ry_res_71.90	1573	27	8
X1ry_res_91.05	1573	15	7.5
X1ry_res_06.15	1573	11	6
HH_Moving_Time_lt2y	1573	11	2.8
HH_Moving_Time_2to4y	1573	18	4.4
HH_Moving_Time_5to9y	1573	17	2
HH_Moving_Time_10to19y	1573	21	2.6
HH_Moving_Time_20to29y	1573	12	1.9
HH_Moving_Time_gt30y	1573	21	7.3
X1ry_res_Owner	1573	69	15
X1ry_res_Tenant	1573	19	6.1
X1ry_res_Social	1573	7.6	9
X1ry_res_FreeAcc	1573	1.2	1.6
X1ry_res_Carpark	1573	73	12
X1ry_res_0car	1573	11	6.9
X1ry_res_1car	1573	45	6.5
X1ry_res_2car	1573	36	10
X1ry_res_3.car	1573	7.5	3.3
Pop_per_1ry_res	1573	2.2	0.28
X1ry_res_gt0car	1573	89	6.9
Pop_per_1ry_res_Owner	1573	2.3	0.28
Pop_per_1ry_res_Tenant	1573	2	0.24
Pop_per_1ry_res_Social	1565	2.2	0.41
Pop_per_1ry_res_FreeAcc	1573	1.7	0.36
X1ry_res_Occupancy	1573	19	25
Owners_Occupancy	1573	16	19
Tenant_Occupancy	1573	1.3	2.2
Social_Occupancy	1573	0.82	2.7
FreeAcc_Occupancy	1573	0.067	0.15
Overcrowding_rate	1573	1.9	2.3

Thématique Emploi

	N	Med	IQR
X1564_Workforce_rate	1573	75	4.2
X1524_Workforce_rate	1573	44	7.6
X2554_Workforce_rate	1573	92	3.8
X5564_Workforce_rate	1573	55	7.7
X1564_men_Workforce_rate	1573	78	4
X1524_men_Workforce_rate	1573	48	9.2
X2554_men_Workforce_rate	1573	95	3.2
X5564_men_Workforce_rate	1573	56	9.3
X1564_women_Workforce_rate	1573	73	4.7
X1524_women_Workforce_rate	1573	39	6.5
X2554_women_Workforce_rate	1573	89	4.7
X5564_women_Workforce_rate	1573	53	7.3
X1564_Employed_rate_amg_WF	1573	88	4.6
X1524_Employed_rate_amg_WF	1573	75	8.1
X2554_Employed_rate_amg_WF	1573	90	4.4
X5564_Employed_rate_amg_WF	1573	90	3.7
X1564_men_Employed_rate_amg_WF	1573	89	4.4
X1524_men_Employed_rate_amg_WF	1573	75	8.9
X2554_men_Employed_rate_amg_WF	1573	91	4.1
X5564_men_Employed_rate_amg_WF	1573	91	3.8
X1564_women_Employed_rate_amg_WF	1573	88	4.8
X1524_women_Employed_rate_amg_WF	1573	74	9
X2554_women_Employed_rate_amg_WF	1573	89	4.7
X5564_women_Employed_rate_amg_WF	1573	90	4.1
X1564_Unemployed_rate_amg_WF	1573	12	4.6
X1524_Unemployed_rate_amg_WF	1573	25	8.1
X2554_Unemployed_rate_amg_WF	1573	10	4.4
X5564_Unemployed_rate_amg_WF	1573	10	3.7
X1564_NonWorking_amg_WF	1573	8.7	3.2
X1564_Student_amg_WF	1573	8.3	2.6
X1564_Retired_amg_WF	1573	7.8	3
X1564_OtherInactive_amg_WF	1573	5.1	2.5
X1564_men_Unemplyed_amg_WF	1573	18	9.2
X1564_women_Unemplyed_amg_WF	1573	11	5.8
X1564_Student_amg_NW	1573	25	9.1
X1564_Retired_amg_NW	1573	24	9.1
X1564_OtherInactive_amg_NW	1573	15	4.6
X1564_NonWorking_amg_POP	1573	33	7
X1564_Farmers_amg_WF	1573	2.7	5.4
X1564_CraftsBusinessShopkeepers_amg_WF	1573	8.5	4.7
X1564_HihgQualWorkers_amg_WF	1573	10	6
X1564_IntermediateProf_amg_WF	1573	23	6.6
X1564_BlueCollar_amg_WF	1573	23	10
X1564_WhiteCollar_amg_WF	1573	28	6.2
X1564_Farmers_amg_EmpWF	1573	1.6	3.4
X1564_CraftsBusinessShopkeepers_amg_EmpWF	1573	6.6	3
X1564_HihgQualWorkers_amg_EmpWF	1573	9.9	7.7
X1564_IntermediateProf_amg_EmpWF	1573	24	5.9
X1564_BlueCollar_amg_EmpWF	1573	24	11
X1564_WhiteCollar_amg_EmpWF	1573	28	4.6
X15._men_amg_empWF	1573	50	1.6
X15._women_amg_empWF	1573	50	1.6
X15._Salaried_amg_empWF	1573	86	7.6
X15._NonSalaried_amg_empWF	1573	14	7.6
X15._FullTime_amg_empWF	1573	83	3.5
X15._men_amg_salWF	1573	50	2.5
X15._women_amg_salWF	1573	50	2.5
X15._men_amg_nonsalWF	1573	64	4.1
X15._women_amg_nonsalWF	1573	36	4.1
X15._men_amg_FullTimeWF	1573	85	8.3
X15._women_amg_FullTimeWF	1573	15	8.3
X15._FullTime_amg_salWF	1573	82	4.2

Thématique Famille

	N	Med	IQR
SinglePerson_HH	1554	33	8.6
SingleMan_HH	1554	15	3.7
SingleWoman_HH	1554	18	5.4
OtherNoFamily_HH	1554	1.5	0.68
Family_HH	1554	65	8.9
NoChildFamily_HH	1573	45	9.2
ChildFamily_HH	1573	41	8.8
SingleParent_HH	1573	13	4.8
Farmer_HH	1554	1.3	2.4
CraftsBusinessShopkeepers_HH	1554	4.9	2
HighQualidied_HH	1554	6.8	6
Intermediate_HH	1554	15	5.5
BlueCollar_HH	1554	16	7.6
WhiteCollar_HH	1554	16	3.2
Retired_HH	1554	32	9.1
Other_HH	1554	4	2.7
X15._SinglePerson_HH	1573	38	6.9
Pop_SingleMan_HH	1554	6.7	2.4
Pop_SingleWoman_HH	1554	8.2	3.4
Pop_OtherNoFamily_HH	1554	1.5	0.77
Pop_Family_HH	1554	83	6.1
Pop_NoChildFamily_HH	1554	32	8.4
Pop_ChildFamily_HH	1554	55	8.9
Pop_SingleParent_HH	1554	12	4.3
Pop_Farmer_HH	1554	1.5	2.9
Pop_CraftsBusinessShopkeepers_HH	1554	6.1	2.3
Pop_HighQualidied_HH	1554	8.2	7.1
Pop_Intermediate_HH	1554	17	5.5
Pop_BlueCollar_HH	1554	19	9.1
Pop_WhiteCollar_HH	1554	17	3.6
Pop_Retired_HH	1554	22	8
Pop_Other_HH	1554	3.1	2.3
X1524_amg_15.POP	1573	12	3.1
X2554_amg_15.POP	1573	45	7.3
X5579_amg_15.POP	1573	35	6.9
X80._amg_15.POP	1573	7.9	3.4
X15._Single_amg_POP	1573	23	4.6
X15._Married_amg_POP	1573	46	4.6
X15._nonMarried_amg_POP	1573	54	4.6
X1524_amg_HH	1573	12	3
X2554_amg_HH	1573	46	7.2
X5579_amg_HH	1573	35	7.1
X80._amg_HH	1573	6.9	3
X1524_amg_Single	1573	3.5	2.5
X2554_amg_Single	1573	31	7.7
X5579_amg_Single	1573	45	6.1
X80._amg_Single	1573	19	5.3
Family_w_Children_amg_HH	1573	55	9.2
Single_Parent_Family_amg_HH	1573	13	4.8
Family_wo_Children_amg_HH	1573	45	9.2

Thématique Revenus

	N	Med	IQR
D1_st_Living	1546	12120	2128
Median_st_Living	1563	21210	3020
D9_st_Living	1546	34980	6435
Interdecile_91_Ratio	1546	2.9	0.57
Taxable_HH	1546	48	14
Poverty_amg_Owners	1460	7	4.4
Poverty_amg_Tenants	1498	26	10
X.30_Poverty	758	21	9.6
X3039_Poverty	1255	16	9.3
X4049_Poverty	1380	15	8.8
X5059_Poverty	1309	14	7.4
X6074_Poverty	1203	9.8	5.2
X75._Poverty	879	11	5.5
Poverty	1526	13	6.9
Activity_Income	1546	71	14
Salary_Income	1546	62	16
Unemployment_Benef	1546	2.8	0.7
Self.Employment	1546	5.7	2.6
Pensions_Annuities	1546	30	10
Estate	1546	9.4	2.7
Social_Benef	1546	5.1	2
Family_Benef	1546	2.1	0.7
Social_Minima	1546	1.9	1.2
Housing_Benef	1546	1.1	0.6
Tax	1546	-16	3.3

Thématique Activité

	N	Med	IQR
Wk_Res_Municipality	1573	27	17
Wk_Res_County.Municipality	1573	54	25
Wk_Res_Region.County	1573	4.8	13
Wk_Res_Country.Region	1573	1.7	2
Wk_Dom_Com_Abroad	1573	0.18	0.23
noTransport_toWk	1573	4.7	3
Walk_toWk	1573	5	3.3
Bike_toWk	1573	1	1
Motorbike_toWk	1573	1.1	0.73
Drive_toWk	1573	83	8.9
PublicTrans_toWk	1573	3.1	6.1
X15._Men_amg_salWF	1573	50	2.5
X15._Women_amg_salWF	1573	50	2.5
X15._PermanentContract_amg_salWF	315	83	5.8
X15._ShortTermContract_amg_salWF	315	11	5.4
X15._InterimContract_amg_salWF	315	1.1	1.5
X15._SubsidizedWork_amg_salWF	315	1.2	1.5
X15._ApprenticeContract_amg_salWF	315	2.3	1.6
X15._SelfEmployed_amg_nonsalWF	315	64	11
X15._Employers_amg_nonsalWF	315	35	11
X15._caregivers_amg_nonsalWF	315	0.89	2

Thématique Formation

	N	Med	IQR
X0205_School	1573	74	5
X0610_School	1573	98	0.97
X1114_School	1573	98	0.78
X1517_School	1573	96	2.1
X1824_School	1573	38	17
X2529_School	1573	3.5	3
X30._School	1573	0.66	0.34
X15._NoDiploma_amg_WF	1573	23	8.4
X15._CertifGeneEducation_amg_WF	1573	5.6	1.4
X15._VocationalGraduate_amg_WF	1573	28	7
X15._HighSchoolGraduate_amg_WF	1573	17	2.1
X15._HSG.2_amg_WF	1573	11	3.1
X15._HSG.4_amg_WF	1573	7.7	3.7
X15._HSG.5._amg_WF	1573	5.8	5.1
X15._HighEducation_amg_WF	1573	25	12
X15._men_NoDiploma_amg_mWF	1573	20	7.4
X15._men_VocationalGraduate_amg_mWF	1573	34	9.6
X15._men_HighSchoolGraduate_amg_mWF	1573	17	2.2
X15._men_HighEducation_amg_mWF	1573	23	12
X15._women_NoDiploma_amg_wWF	1573	25	9.5
X15._women_VocationalGraduate_amg_wWF	1573	23	4.9
X15._women_HighSchoolGraduate_amg_wWF	1573	18	2.3
X15._women_HighEducation_amg_wWF	1573	26	12
X15._MenOnWomen_NoDiploma	1573	76	13
X15._MenOnWomen_VocationalGraduate	1573	135	25
X15._MenOnWomen_HighSchoolGraduate	1573	89	10
X15._MenOnWomen_HighEducation	1573	82	8.5

Thématique Population

	N	Med	IQR
X0014_amg_POP	1573	18	3.7
X1529_amg_POP	1573	18	3.7
X3044_amg_POP	1573	18	3.2
X4559_amg_POP	1573	21	1.7
X6074_amg_POP	1573	18	4.8
X7589_amg_POP	1573	8.7	3.6
X90._amg_POP	1573	1.3	0.77
Men	1573	49	1.3
X0019_amg_POP	1573	23	4.3
X2064_amg_POP	1573	55	3.9
X65._amg_POP	1573	21	7.8
X15._Farmers_amg_POP	1573	0.95	1.9
X15._CraftsBusinessShopkeeper_amg_POP	1573	3.8	1.5
X15._ManagersHigherIntellectProf_amg_POP	1573	5.6	5
X15._IntermediateProf_amg_POP	1573	13	4.8
X15._WhiteCollar_amg_POP	1573	16	2.7
X15._BlueCollar_amg_POP	1573	13	5.8
X15._Retired_amg_POP	1573	30	9.5
X15._OtherNoActivity_amg_POP	1573	14	4.4
X0014_men_amg_mPOP	1573	18	3.8
X1529_men_amg_mPOP	1573	15	3.6
X3044_men_amg_mPOP	1573	18	3
X4559_men_amg_mPOP	1573	21	1.9
X6074_men_amg_mPOP	1573	18	5.2
X7589_men_amg_mPOP	1573	7.3	3.2
X90._men_amg_mPOP	1573	0.73	0.47
X0019_men_amg_mPOP	1573	25	4.6
X2064_men_amg_mPOP	1573	55	3.5
X65._men_amg_mPOP	1573	19	7.2
X15._men_Farmers_amg_mPOP	1573	1.5	2.9
X15._men_CraftsBusinessShopkeeper_amg_mPOP	1573	5.6	2.2
X15._men_ManagersHigherIntellectProf_amg_mPOP	1573	6.8	6.5
X15._men_IntermediateProf_amg_mPOP	1573	13	4.6
X15._men_WhiteCollar_amg_mPOP	1573	7.2	3.1
X15._men_BlueCollar_amg_mPOP	1573	22	8.5
X15._men_Retired_amg_mPOP	1573	29	8.9
X15._men_OtherNoActivity_amg_POP	1573	11	3.7
X0014_women_amg_wPOP	1573	17	3.8
X1529_women_amg_wPOP	1573	14	3.5
X3044_women_amg_wPOP	1573	18	3.5
X4559_women_amg_wPOP	1573	20	1.7
X6074_women_amg_wPOP	1573	18	4.6
X7589_women_amg_wPOP	1573	9.9	4.1
X90._women_amg_wPOP	1573	1.9	1.1
X0019_women_amg_wPOP	1573	22	4.4
X2064_women_amg_wPOP	1573	54	4.5
X65._women_amg_wPOP	1573	23	8.3
X15._women_Farmers_amg_wPOP	1573	0.44	0.97
X15._women_CraftsBusinessShopkeeper_amg_wPOP	1573	2.1	1
X15._women_ManagersHigherIntellectProf_amh_wPOP	1573	4.5	3.7
X15._women_IntermediateProf_amg_wPOP	1573	14	5.2
X15._women_WhiteCollar_amg_wPOP	1573	24	4.1
X15._women_BlueCollar_amg_wPOP	1573	4.8	3.2
X15._women_Retired_amg_wPOP	1573	30	10
X15._women_OtherNoActivity_amg_wPOP	1573	16	5.2

Thématique Logement

	N	Med	IQR
X1ry_res	1573	85	15
X2ry_res	1573	5.6	11
Vacant_Home	1573	8.4	4.2
Houses	1573	78	32
Flats	1573	21	32
Nb_Rooms_1ry_res	1573	4.4	0.57
House_1ry_res	1573	79	29
Flat_1ry_res	1573	20	28
X1ry_res_bf_1919	1573	16	15
X1ry_res_19.45	1573	7.9	4.7
X1ry_res_46.70	1573	16	9.6
X1ry_res_71.90	1573	27	8
X1ry_res_91.05	1573	15	7.5
X1ry_res_06.15	1573	11	6
HH_Moving_Time_lt2y	1573	11	2.8
HH_Moving_Time_2to4y	1573	18	4.4
HH_Moving_Time_5to9y	1573	17	2
HH_Moving_Time_10to19y	1573	21	2.6
HH_Moving_Time_20to29y	1573	12	1.9
HH_Moving_Time_gt30y	1573	21	7.3
X1ry_res_Owner	1573	69	15
X1ry_res_Tenant	1573	19	6.1
X1ry_res_Social	1573	7.6	9
X1ry_res_FreeAcc	1573	1.2	1.6
X1ry_res_Carpark	1573	73	12
X1ry_res_0car	1573	11	6.9
X1ry_res_1car	1573	45	6.5
X1ry_res_2car	1573	36	10
X1ry_res_3.car	1573	7.5	3.3
Pop_per_1ry_res	1573	2.2	0.28
X1ry_res_gt0car	1573	89	6.9
Pop_per_1ry_res_Owner	1573	2.3	0.28
Pop_per_1ry_res_Tenant	1573	2	0.24
Pop_per_1ry_res_Social	1565	2.2	0.41
Pop_per_1ry_res_FreeAcc	1573	1.7	0.36
X1ry_res_Occupancy	1573	19	25
Owners_Occupancy	1573	16	19
Tenant_Occupancy	1573	1.3	2.2
Social_Occupancy	1573	0.82	2.7
FreeAcc_Occupancy	1573	0.067	0.15
Overcrowding_rate	1573	1.9	2.3

Thématique Immigration

	N	Med	IQR
French_nlty	1239	96	5.3
Stranger	1239	4	5.3
Immigrant	1554	5.4	6.1
French_nlty_amg_Men	1239	96	5.5
Stranger_amg_Men	1239	4.1	5.5
Immigrant_amg_Men	1554	5.4	6.2
French_nlty_amg_Women	1239	96	5.1
Stranger_amg_Women	1239	3.8	5.1
Immigrant_amg_Women	1554	5.5	6.2
Res_Abroad_2017	1239	0.25	0.26

Thématique Géographie

	N	Med	IQR
densite	1897	58	105
latitude	1231	6652162	408167
longitude	1231	676107	330745
SO.NE	1231	1	0.46
NO.SE	1231	-0.021	0.46

Manhattan

Pour construire les graphiques suivants, chaque variable a été dichotomisée par rapport à la médiane (1 pour supérieur à la médiane et 0 pour inférieur à la médiane).

Pour chaque semaine de l’année 2021, les 25 % des territoires les moins vaccinés sont étiquetés 1 et les autres 0.

On calcule l’odds ratio pour chaque variable. Cela permet de repérer les variables qui agissent le plus sur le taux de vaccination.

Dans ls graphique suivants, chaque variable a une position fixe sur l’axe des abscisses.

L’axe des ordonnées représente le maximum entre l’odds ratio et son inverse. Ainsi une variable qui agit fortement sur le taux de vaccination aura une position élevée sur le graphque indépendamment de l’influence positive ou négative de son influence. Les variables sont classées par thématique.

La grosseur de chaque point est proportionnelle à \(-\log_{10}(p)\).

Puis pour connaitre l’influebce de chaque variable, on ne trace uniquement l’odds ratio et enfin son inverse.

Données cumulées

Données à la semaine non cumulées

Par classe d’âge

0 - 19 ans

20 - 39 ans

40 - 54 ans

55 - 64 ans

65 - 74 ans

75 ans et plus